We design and analyze Variance-Aware-Lower Upper Confidence Bound (VA-LUCB), a parameter-free algorithm, for identifying the best arm under fixed-confidence setup stringent constraint that variance of chosen is strictly smaller than given threshold. An upper bound on VA-LUCB’s sample complexity shown to be characterized by fundamental variance-aware hardness quantity <inline-formula xmlns:mml="...

Abstract Factor analysis proposes an alternative approach to standard portfolio theory: the latter is optimisation based, while former estimation based. Also, in theory, returns are only explained by volatility factor, factor a multiplicity of factors, which managers can choose from tilt their portfolios. In attempting reconcile these worlds, we propose penalised utility function, incorporating...

AIMS The aim of this study was to investigate the current prenatal "off-label use" of cytomegalovirus hyperimmunoglobulin (CMV-HIG) in the prevention and treatment of congenital CMV (cCMV) infection, including the long-term outcome of the children. METHODS This retrospective observational study comprised mothers and their children, born between January 1, 2006, and October 30, 2010. Prenatal ...

A memetic approach that combines a genetic algorithm (GA) and quadratic programming is used to address the problem of optimal portfolio selection with cardinality constraints and piecewise linear transaction costs. The framework used is an extension of the standard Markowitz mean–variance model that incorporates realistic constraints, such as upper and lower bounds for investment in individual ...

Background: Bin packing is an NP hard optimization problem of packing items of given sizes into minimum number of capacity limited bins. Besides the basic problem, numerous other variants of bin packing exist. The cardinality constrained bin packing adds an additional constraint that the number of items in a bin must not exceed a given limit Nmax. Objectives: Goal of the paper is to present a p...